Hepatic Gene Expression Analysis

22160 R for bio data science

Antoine Andréoletti, Olivier Gaufrès, Amy Surry, Lea Skytthe, and Trine Søgaard

Introduction

Aim

Investigating hepatic gene expression by comparing expression levels across:

  • Healthy individuals
  • Patients with NAFLD
  • Patients with cirrhosis

Data

  • RNA-seq: from patients with NAFLD, patients with cirrhosis, and healthy controls under both fasting and postprandial conditions
  • Meta data: additional information about patients

Data processing

Data processing

Methods



Descriptive analysis


  • Distributions are fairly equal throughout our data
  • Sick people are older on average
  • No significance in disease between men and women

PCA & Heatmap


  • item1
  • item2
  • item3

Differential Expression Analysis


Compare gene expression levels between groups using DESeq2


Output:

  • Global Mean
  • Fold-change
  • Adjusted-p-value

Gene Set Enrichment Analysis


Investigating hepatic gene set enrichment


  • C11 hepatocytes is a subtype of hepatocytes (1 of 3)
  • Hepatocytes produces hepatokines (hormone involved in metabolic regulation)
  • Some therapies try to promote hepatocyte regeneration



Discussion / Conclusion

  • Key points
  • Count_data derived from micro-array
  • Troubles with DESeq2 package and dplyr
  • Key points

Group 20